Managing Very Large Databases and Data Warehousing

Managing Very Large Databases and Data Warehousing

Major libraries have large collections and circulation. Managing libraries electronically has resulted in the creation and management of large library databases. The interconnection of libraries and sharing resources across libraries has resulted in the management of very large databases. Most large and/or multinational industries worldwide have exploited such opportunities by applying data war...

Multidimensional Databases and Data Warehousing

Managing Very Large Scienti c Data

We discuss issues in managing very large scientiic data collections and describe our approach at the San Diego Supercomputer Center for supporting high performance data-intensive applications. Our systems provide metadata-based access to data sets and support collections with widely varying data characteristics.

Querying Hierarchical Data in Very Large Databases

Hierarchical data, such as Partially Ordered Set (POSET) is tremendously used in relational databases, especially in data mining and data warehouse based-applications. Unfortunately, SQL (Structured Query Language) does not effectively support hierarchical data structure to manage this sort of data, for example, in Oracle, a CONNECT BY operator is used to query data organized into trees, howeve...

Mining Very Large Databases

38 Computer E stablished companies have had decades to accumulate masses of data about their customers , suppliers, and products and services. The rapid pace of e-commerce means that Web startups can become huge enterprises in months, not years, amassing proportionately large databases as they grow. Data mining, also known as knowledge discovery in databases, 1 gives organizations the tools to ...